Therapies for breast cancer (BC) should be guided by biological features, such as endocrine or HER2/neu dependence. Pre-clinical and early clinical data suggest synergism between PI3K/Akt and EGFR signaling inhibition in BC. We hypothesize that BC with low PTEN levels or Akt hyperactivation will have a higher response to combined blockade of the EGFR and PI3K/Akt signaling, and the microarray analysis of tumors that respond to the treatment combination will resemble established EGFR and PI3K/Akt/mTOR dependence gene signatures. As a future independent breast cancer translational researcher, with the necessary mentorship from Dr. Arteaga and Dr. Rothenberg and full institutional support beyond the allowable costs of this award, I propose a clinical trial in the metastatic setting, in which the correlative studies would help predict clinical responses, impacting future patient selection and trial design. In this research proposal, we will: (1) Determine the safety profile and efficacy of the mTOR inhibitor everolimus and the EGFR inhibitor erlotinib combination in a phase l/ll clinical trial for patients with metastatic BC; (2) Determine biomarkers of response to the erlotinib/everolimus combination in BC. PTEN, pAkt, pS6, and EGFR (IHC) and PI3K mutations on exons 9 and 20 sequenced in collected paraffin blocks will be correlated with clinical outcome in Aim 1; and (3) Determine if gene expression profiling can identify gene expression signatures that will predict sensitivity to EGFR and mTOR inhibitors. We will identify a signature suggestive of EGFR and mTOR dependence using the clinical outcome on the clinical trial as the supervising parameter, in addition to mining the generated data sets from all collected material to answer if previously established EGFR and PI3K/Akt/mTOR gene signatures will predict response to treatment. We will also correlate IHC results of Aim 2 with the subtypes of breast cancer determined by molecular classification based on their gene expression (luminal A, luminal B, HER2?, and basal-like). Relevance to public: This research will focus on discovery of a molecular signature based on genes and proteins involved in breast cancer's growth and survival, which will help identify groups of breast cancer patients that may benefit from new treatment combinations that target these particular genes and proteins. This research could impact design of future clinical trials, their answers could ultimately reduce breast cancer mortality.